Conventionally, it has been demonstrated that a neural network apparatus formed in order to realize functions similar to those of a biological neural network has excellent data processing functions such as pattern recognition and the like and, in connection with this, various studies have been under way from the points of both hardware and software. In particular, as to the hardware, there have been available one using electric circuit and one using light. Among the former, one in which the biological neural tissue is simulated to prepare a synapse or cell by using silicon MOS, or one in which they are prepared by using a superconductive circuit including Josephson junction has been experimentally made or proposed.
It is true that a neural network can be realized and is considered realizable according to the conventional proposal, but its number of neuron devices is still small. Therefore, in order to allow a practical extensive application, it is necessary to further improve the degree of integration. A problem with this integration is that the number of connections between the devices amounts to a vast one. According to the conventionally proposed ones, the circuit forming the synapse becomes too large and, accordingly, the operation delay time at the synapse portion also becomes great resulting in a large computing time and trouble.